The parameter estimation analyses of the events produce samples of the posterior probability density function in the form of Markov chains. Successive states of these chains are not independent, as Markov processes depend on the previous state [1]}. Independent samples are obtained from the full Markov chains by “thinning” or drawing samples from chains of the coldest temperature, with an interval of the autocorrelation length [2]}, [1]}. These independent samples are used to calculate estimates for the model parameters from the analysis.
